Literature DB >> 28987905

Neural processing of musical meter in musicians and non-musicians.

T Christina Zhao1, H T Gloria Lam2, Harkirat Sohi3, Patricia K Kuhl4.   

Abstract

Musical sounds, along with speech, are the most prominent sounds in our daily lives. They are highly dynamic, yet well structured in the temporal domain in a hierarchical manner. The temporal structures enhance the predictability of musical sounds. Western music provides an excellent example: while time intervals between musical notes are highly variable, underlying beats can be realized. The beat-level temporal structure provides a sense of regular pulses. Beats can be further organized into units, giving the percept of alternating strong and weak beats (i.e. metrical structure or meter). Examining neural processing at the meter level offers a unique opportunity to understand how the human brain extracts temporal patterns, predicts future stimuli and optimizes neural resources for processing. The present study addresses two important questions regarding meter processing, using the mismatch negativity (MMN) obtained with electroencephalography (EEG): 1) how tempo (fast vs. slow) and type of metrical structure (duple: two beats per unit vs. triple: three beats per unit) affect the neural processing of metrical structure in non-musically trained individuals, and 2) how early music training modulates the neural processing of metrical structure. Metrical structures were established by patterns of consecutive strong and weak tones (Standard) with occasional violations that disrupted and reset the structure (Deviant). Twenty non-musicians listened passively to these tones while their neural activities were recorded. MMN indexed the neural sensitivity to the meter violations. Results suggested that MMNs were larger for fast tempo and for triple meter conditions. Further, 20 musically trained individuals were tested using the same methods and the results were compared to the non-musicians. While tempo and meter type similarly influenced MMNs in both groups, musicians overall exhibited significantly reduced MMNs, compared to their non-musician counterparts. Further analyses indicated that the reduction was driven by responses to sounds that defined the structure (Standard), not by responses to Deviants. We argue that musicians maintain a more accurate and efficient mental model for metrical structures, which incorporates occasional disruptions using significantly fewer neural resources.
Copyright © 2017 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Duple vs. triple meter; EEG; Music training; Musical meter; Tempo; Temporal structure

Mesh:

Year:  2017        PMID: 28987905     DOI: 10.1016/j.neuropsychologia.2017.10.007

Source DB:  PubMed          Journal:  Neuropsychologia        ISSN: 0028-3932            Impact factor:   3.139


  6 in total

1.  Impact of music-based intervention on verbal memory: an experimental behavioral study with older adults.

Authors:  Veronika Diaz Abrahan; Favio Shifres; Nadia Justel
Journal:  Cogn Process       Date:  2020-09-21

2.  Violation of rhythmic expectancies can elicit late frontal gamma activity nested in theta oscillations.

Authors:  M Edalati; M Mahmoudzadeh; J Safaie; F Wallois; S Moghimi
Journal:  Psychophysiology       Date:  2021-07-26       Impact factor: 4.348

3.  Do musicians learn a fine sequential hand motor skill differently than non-musicians?

Authors:  Jagna Sobierajewicz; Ryszard Naskręcki; Wojciech Jaśkowski; Rob H J Van der Lubbe
Journal:  PLoS One       Date:  2018-11-21       Impact factor: 3.240

4.  Event-Related Potential Evidence of Implicit Metric Structure during Silent Reading.

Authors:  Mara Breen; Ahren B Fitzroy; Michelle Oraa Ali
Journal:  Brain Sci       Date:  2019-08-08

5.  Switching perception of musical meters by listening to different acoustic cues of biphasic sound stimulus.

Authors:  Sotaro Kondoh; Kazuo Okanoya; Ryosuke O Tachibana
Journal:  PLoS One       Date:  2021-08-30       Impact factor: 3.240

6.  Neural and physiological relations observed in musical beat and meter processing.

Authors:  T Christina Zhao; Patricia K Kuhl
Journal:  Brain Behav       Date:  2020-09-12       Impact factor: 2.708

  6 in total

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